A comparative study on dimensionality reduction between principal component analysis and k-means clustering
The curse of dimensionality and the empty space phenomenon emerged as a critical problem in text classification. One way of dealing with this problem is applying a feature selection technique before performing a classification model. This technique helps to reduce the time complexity and sometimes i...
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| Päätekijät: | , , |
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| Aineistotyyppi: | EJournal Article |
| Julkaistu: |
Institute of Advanced Engineering and Science,
2019-11-01.
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| Hyllypaikka: |
A1234.567 |
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| Nide 1 | Saatavissa |